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Quantifying the temperature sensitivity of methane (CH₄) production is crucial for predicting how wetland ecosystems will respond to climate warming. Typically, the temperature sensitivity (often quantified as a Q₁₀value) is derived from laboratory incubation studies and then used in biogeochemical models. However, studies report wide variation in incubation-inferred Q₁₀values, with a large portion of this variation remaining unexplained. Here we applied observations in a thawing permafrost peatland (Stordalen Mire) and a well-tested process-rich model (ecosys) to interpret incubation observations and investigate controls on inferred CH₄production temperature sensitivity. We developed a field-storage-incubation modeling approach to mimic the full incubation sequence, including field sampling at a particular time in the growing season, refrigerated storage, and laboratory incubation, followed by model evaluation. We found that CH₄production rates during incubation are regulated by substrate availability and active microbial biomass of key microbial functional groups, which are affected by soil storage duration and temperature. Seasonal variation in substrate availability and active microbial biomass of key microbial functional groups led to strong time-of-sampling impacts on CH₄production. CH₄production is higher with less perturbation post-sampling, i.e. shorter storage duration and lower storage temperature. We found a wide range of inferred Q₁₀values (1.2–3.5), which we attribute to incubation temperatures, incubation duration, storage duration, and sampling time. We also show that Q₁₀values of CH₄production are controlled by interacting biological, biochemical, and physical processes, which cause the inferred Q₁₀values to differ substantially from those of the component processes. Terrestrial ecosystem models that use a constant Q₁₀value to represent temperature responses may therefore predict biased soil carbon cycling under future climate scenarios.

 

Abstract. Canopy stomatal conductance is commonly estimated fromeddy covariance measurements of the latent heat flux (LE) by inverting thePenman–Monteith equation. That method ignores eddy covariance measurementsof the sensible heat flux (H) and instead calculates H implicitly as theresidual of all other terms in the site energy budget. Here we show thatcanopy stomatal conductance is more accurately calculated from eddy covariance (EC)measurements of both H and LE using the flux–gradient equations that defineconductance and underlie the Penman–Monteith equation, especially when thesite energy budget fails to close due to pervasive biases in the eddy fluxesand/or the available energy. The flux–gradient formulation dispenses withunnecessary assumptions, is conceptually simpler, and is as or more accuratein all plausible scenarios. The inverted Penman–Monteith equation, on theother hand, contributes substantial biases and erroneous spatial andtemporal patterns to canopy stomatal conductance, skewing its relationshipswith drivers such as light and vapor pressure deficit. 

Both plant physiology and atmospheric chemistry are substantially altered by the emission of volatile isoprenoids (VI), such as isoprene and monoterpenes, from plant leaves. Yet, since gaining scientific attention in the 1950’s, empirical research on leaf VI has been largely confined to laboratory experiments and atmospheric observations. Here, we introduce a new field instrument designed to bridge the scales from leaf to atmosphere, by enabling precision VI detection in real time from plants in their natural ecological setting. With a field campaign in the Brazilian Amazon, we reveal an unexpected distribution of leaf emission capacities (EC) across the vertical axis of the forest canopy, with EC peaking in the mid-canopy instead of the sun-exposed canopy surface, and moderately high emissions occurring in understory specialist species. Compared to the simple interpretation that VI protect leaves from heat stress at the hot canopy surface, our results encourage a more nuanced view of the adaptive role of VI in plants. We infer that forest emissions to the atmosphere depend on the dynamic microenvironments imposed by canopy structure, and not simply on canopy surface conditions. We provide a new emissions inventory from 52 tropical tree species, revealing moderate consistency in EC within taxonomic groups. We highlight priorities in leaf volatiles research that require field-portable detection systems. Our self-contained, portable instrument provides real-time detection and live measurement feedback with precision and detection limits better than 0.5 nmol VI m –2 leaf s –1 . We call the instrument ‘PORCO’ based on the gas detection method: photoionization of organic compounds. We provide a thorough validation of PORCO and demonstrate its capacity to detect ecologically driven variation in leaf emission rates and thus accelerate a nascent field of science: the ecology and ecophysiology of plant volatiles. 

Canopy stomatal conductance (gsV) is commonly estimated from eddy covariance (EC) measurements of latent heat flux (LE) by inverting the Penman-Monteith (PM) equation. That method implicitly represents the sensible heat flux (H) as the residual of all other terms in the site energy budget – even though H is measured at least as accurately as LE at every EC site while the rest of the energy budget almost never is. We argue that gsV should instead be calculated from EC measurements of both H and LE, using the flux-gradient formulation that defines conductance and underlies the PM equation. The flux-gradient formulation dispenses with unnecessary assumptions, is conceptually simpler, and provides more accurate values of gsV for all plausible scenarios in which the measured energy budget fails to close, as is common at EC sites. The PM equation, on the other hand, contributes biases and erroneous spatial and temporal patterns to gsV, skewing its relationships with drivers such as light and vapor pressure deficit. To minimize the impact of the energy budget closure problem on the PM equation, it was previously proposed that the eddy fluxes should be corrected to close the long-term energy budget while preserving the Bowen ratio (B = H/LE). We show that such a flux correction does not fully remedy the PM equation but should produce accurate values of gsV when combined with the flux-gradient formulation. 

Understanding the effects of intensification of Amazon basin hydrological cycling—manifest as increasingly frequent floods and droughts—on water and energy cycles of tropical forests is essential to meeting the challenge of predicting ecosystem responses to climate change, including forest “tipping points”. Here, we investigated the impacts of hydrological extremes on forest function using 12+ years of observations (between 2001–2020) of water and energy fluxes from eddy covariance, along with associated ecological dynamics from biometry, at the Tapajós National Forest. Measurements encompass the strong 2015–2016 El Niño drought and La Niña 2008–2009 wet events. We found that the forest responded strongly to El Niño‐Southern Oscillation (ENSO): Drought reduced water availability for evapotranspiration (ET) leading to large increases in sensible heat fluxes (H). PartitioningETby an approach that assumes transpiration (T) is proportional to photosynthesis, we found that water stress‐induced reductions in canopy conductance (G_s) droveTdeclines partly compensated by higher evaporation (E). By contrast, the abnormally wet La Niña period gave higherTand lowerE, with little change in seasonalET. Both El Niño‐Southern Oscillation (ENSO) events resulted in changes in forest structure, manifested as lower wet‐season leaf area index. However, only during El Niño 2015–2016, we observed a breakdown in the strong meteorological control of transpiration fluxes (via energy availability and atmospheric demand) because of slowing vegetation functions (via shutdown ofG_sand significant leaf shedding). Drought‐reducedTandG_s, higherHandE, amplified by feedbacks with higher temperatures and vapor pressure deficits, signaled that forest function had crossed a threshold, from which it recovered slowly, with delay, post‐drought. Identifying such tipping point onsets (beyond which future irreversible processes may occur) at local scale is crucial for predicting basin‐scale threshold‐crossing changes in forest energy and water cycling, leading to slow‐down in forest function, potentially resulting in Amazon forests shifting into alternate degraded states.

 

Biodiversity contributes to the ecological and climatic stability of the Amazon Basin1,2, but is increasingly threatened by deforestation and fire3,4. Here we quantify these impacts over the past two decades using remote-sensing estimates of fire and deforestation and comprehensive range estimates of 11,514 plant species and 3,079 vertebrate species in the Amazon. Deforestation has led to large amounts of habitat loss, and fires further exacerbate this already substantial impact on Amazonian biodiversity. Since 2001, 103,079–189,755 km2 of Amazon rainforest has been impacted by fires, potentially impacting the ranges of 77.3–85.2% of species that are listed as threatened in this region5. The impacts of fire on the ranges of species in Amazonia could be as high as 64%, and greater impacts are typically associated with species that have restricted ranges. We find close associations between forest policy, fire-impacted forest area and their potential impacts on biodiversity. In Brazil, forest policies that were initiated in the mid-2000s corresponded to reduced rates of burning. However, relaxed enforcement of these policies in 2019 has seemingly begun to reverse this trend: approximately 4,253–10,343 km2 of forest has been impacted by fire, leading to some of the most severe potential impacts on biodiversity since 2009. These results highlight the critical role of policy enforcement in the preservation of biodiversity in the Amazon.